The CD4 cell count is used as a marker of immune status and, in the past, was used as a guide for initiating antiretroviral therapy (ART) in people living with human immunodeficiency virus (PLHIV). Over the past years, HIV management guidelines have shifted from initiating therapy at criteria of a CD4 cell count ≤ 200 cells/m³ to universal test and treat (UTT). It was anticipated that only a small proportion of patients would present with a baseline CD4 count ≤ 200 cells/m³ and/or manifestations of opportunistic infections.

The total study sample comprised 241 patients (112 vs. 129 in Cohorts 1 and 2, respectively). Most patients were between 26 and 35 (36.6% vs. 51.9%, p < 0.001 in Cohorts 1 and 2, respectively). The patients in the study were predominantly female, with the racial distribution being primarily black African (see Table 1).

Table 2 presents the differences in median CD4 cell counts between two cohorts at two time points: baseline and after 1 year. At baseline, Cohort 1 had a lower median CD4 cell count of 170 cells/mm³ (interquartile range [IQR]: 85.5–287) than Cohort 2, with a median count of 243 cells/mm³ (IQR: 120–411). After 1 year, the CD4 cell counts increased to 332.50 cells/mm³ (IQR: 228–517.5) and 372 cells/mm³ (IQR: 222–579) in Cohorts 1 and 2, respectively. However, the difference between the two cohorts was not statistically significant (p = 0.680).

Table 3 presents the frequency distribution of CD4 cell counts at baseline, the 1-year follow-up for Cohorts 1 and 2, and the corresponding p-values for both cohorts. In Cohort 1, at baseline, 57.1% of patients had a CD4 cell count of less than 200 cells/mm³ (p < 0.001). After 1 year of treatment, there was a notable improvement, with 45.5% of patients achieving CD4 cell counts above 350 cells/mm³. The differences observed between the CD4 categories in Cohort 1 were statistically significant (p < 0.001). In Cohort 2, at baseline, 41.9% of patients had a CD4 cell count of fewer than 200 cells/mm³, which was higher than the proportion of patients with CD4 cell counts between 200 cells/mm³ and 350 cells/mm³ (23.3%), and those with CD4 cell counts above 350 cells/mm³ (34.9%) (p = 0.033). After 1 year of treatment, most patients achieved CD4 cell counts above 350 cells/mm³ (55.8%).

The study captured opportunistic infection present at diagnosis and during the period under review. It showed TB (both pulmonary and disseminated) as the predominant OI with the highest prevalence of TB infections in the group with CD4 cell count < 200 mm³ in both Cohort 1 (29 cases) and Cohort 2 (36 cases), p = 0.039 (see Table 4).

Table 5 demonstrates that in Cohort 1, 77.7% and Cohort 2, 81.4% of the patients achieved virological suppression at 1 year post-ART initiation. This was statistically significant within each cohort (p < 0.001); however, there was no significant difference between the two cohorts (p = 0.475).

This study presented an examination of individuals who commenced ART for HIV infection at distinct target CD4 levels, as suggested by the prevailing HIV treatment guidelines during that period.

Importantly, this sample of patients’ index testing and diagnosis for HIV occurred at a tertiary institution after referral from surrounding healthcare centres to various specialities. The study scrutinised these patients’ initial CD4 cell counts upon their presentation and subsequently assessed their CD4 levels again after 1 year. Additionally, the study assessed the prevalence of virological suppression among these patients at 1 year. Furthermore, the investigation characterised the profile of opportunistic infections observed in this sample of HIV-positive individuals.

South Africa continues to grapple with a substantial HIV epidemic, with KZN emerging as one of the provinces facing a disproportionate burden of the disease, particularly among the younger population.²⁷

Our study revealed that the majority of patients in both Cohorts 1 and 2 who initiated therapy fell within the age range of 26–35 years, constituting 36.6% and 51.9% of the respective cohorts. This observed prevalence aligned with the findings of the household-based HIV serosurvey, which documented a higher incidence of infections among individuals aged 25–34 years, with the highest infection rates observed among 26-year-old females.²⁸ The gender distribution in both cohorts primarily comprised females, reflecting the gender distribution patterns observed in South Africa.²⁹

Extensive research indicates that factors such as increased female participation in rural-to-urban migration and socio-economic challenges such as unemployment may contribute to elevated infection rates among women.²⁹ Regarding racial demographics, the study population predominantly consisted of black individuals, accounting for 98.2% in Cohort 1 and 94.6% in Cohort 2, aligning with national epidemiological data and the specific geographical context of the study.³⁰

Over more than two decades, the measurement of CD4 cell count has emerged as a pivotal tool in comprehending the progression of HIV disease and assessing the susceptibility to opportunistic infections.³¹ The development of guidelines concerning initiating ART at higher CD4 cell counts has been influenced by evidence suggesting that deferring treatment until CD4 cell counts decline below 200 cells/mm³ is linked to increased mortality rates.³² These guidelines are formulated with consideration for a population that undergoes annual HIV testing to commence treatment before the onset of immunodeficiency.³³

In Cohort 1, the median CD4 cell count at the initiation of ART was measured at 170.0 mm³ (IQR: 85.50 mm³ – 287.0 mm³, while in Cohort 2, it was recorded as 243.0 mm³ (IQR: 120.00 mm³ – 411.0 mm³).

Despite the implementation of higher CD4 cell count targets and the era of UTT, the study revealed that the majority of patients in both cohorts (57.1% in Cohort 1 and 41.9% in Cohort 2) had CD4 cell counts below 200 cells/mm³ at the time of treatment initiation. A meta-analysis conducted in sub-Saharan Africa, focusing on CD4 cell counts at treatment initiation, indicated that there has been no discernible change in the trend of CD4 cell counts over the past decade, irrespective of the specified threshold.³⁴ This persistent lack of change may be attributable to factors such as reduced uptake of HIV testing because of prevailing HIV-related stigma, as well as geographic- and transportation-related barriers.^35,36

Cohort 2 exhibited a substantially greater proportion of patients with CD4 cell counts exceeding 350 mm³ (34.9%) than Cohort 1 (6.3%). This discrepancy was anticipated, as Cohort 2 represented the UTT era, wherein treatment initiation was not solely based on CD4 cell count thresholds. In contrast, patients in Cohort 1 were initiated on treatment because of alternative indications, such as co-infection with TB or other factors.

The OIs pose a significant threat to the health and survival of individuals living with HIV. Our study revealed a higher prevalence of OIs among patients with CD4 cell counts below 200 cells/mm³, with 31.25% in Cohort 1 and 25.58% in Cohort 2 being affected. Among the observed OIs, TB infection was the most commonly occurring, with higher numbers observed in the more immunodeficient group (30 cases in Cohort 1 vs. 36 cases in Cohort 2). This finding aligned with previous retrospective studies identifying TB and oral candidiasis as the two most common OIs.^37,38 A prospective cohort study conducted by Murphy et al. at Mc Cord Hospital in KZN also reported TB as the predominant OI, accounting for 76% of cases (43). Our study additionally identified other OIs, including herpes zoster (2.9%), bacterial pneumonia (1.2%), candidiasis (2.1%), pneumocystis jiroveci pneumonia (0.4%), and HIV-associated malignancies such as non-Hodgkin’s lymphoma, cervical cancer, and Kaposi’s sarcoma (1.7%). The study also documented cases of syphilis and cryptococcal meningitis (7.1%) among the patients. These findings underscored the diverse range of OIs that can occur in HIV-positive individuals with compromised immune function and emphasised the importance of screening for such infections.

In our study, we found that at the 1-year mark, the median CD4 cell count was 332.50 cells/mm³ (IQR: 228.00–517.50) in Cohort 1 and 372.00 cells/mm³ (IQR: 222.00–579.00) in Cohort 2. These results align with a study conducted by Mocroft et al., which reported a median CD4 count of 204 cells/mm³ (IQR: 85–330) at initiating ART. Mocroft et al. also observed an average increase of 100 cells/mm³ in CD4 count after 1 year of initiating ART.³⁹ Notably, they found that patients with lower baseline CD4 counts exhibited a greater increase in CD4 count compared with those initiating treatment at CD4 counts above 500 cells/mm³.⁴⁰ This highlighted the significance of initiating treatment at higher CD4 counts to preserve immunological function in patients.

In Cohort 1, 87 out of 112 patients (77.67%) achieved virological suppression, while in Cohort 2, 105 out of 124 patients (84.67%) achieved virological suppression. One of the United Nations Joint Programme on HIV/AIDS (UNAIDS) 90-90-90 targets aimed to achieve 90% viral suppression in individuals receiving ART by 2020, with the overall goal of curbing the HIV epidemic by 2030. Our study found no significant difference in the rates of virological suppression between the cohorts (p = 0.475), irrespective of their initial CD4 cell counts. However, within each cohort, there was a significant variation in the number of patients who achieved suppressed viral loads (p < 0.001). It is important to acknowledge that during the study period, the rates of viral suppression did not meet the target. Nevertheless, a notable proportion of patients achieved virological suppression. Factors contributing to virological failure included poor adherence to treatment and the development of opportunistic infections within our cohorts.

This study revealed that, despite a change in the guidelines with the removal of CD4 counts cut-off levels of 350 cells/mm³ before initiating ART, a significant number of patients attending the HIV clinic in King Edward VIII Hospital still present with low CD4 counts at diagnosis, in the UTT era. These findings suggested delays in diagnosis and treatment initiation. However, the reasons for the delay were unknown and beyond the study’s scope, and further studies are required to investigate these barriers. The TB was the most typical OI infection in both cohorts, which in part may be explained by a comparable proportion of those with low CD4 cell counts being at baseline. Furthermore, viral load suppression at 1 year was below the UNAIDS target of 90% in the sample, highlighting the need to reinforce treatment adherence and investigate and address modifiable contributing factors.